research papers

Acta Cryst. (2018). D74, 585–594 https://doi.org/10.1107/S2059798318007945 585

Received 21 December 2017

Accepted 29 May 2018

Keywords: low-abundance imaging; electron

cryotomography; subtomogram averaging;

bacterial flagellar motors; molecular evolution.

Insights into the evolution of bacterial flagellarmotors from high-throughput in situ electroncryotomography and subtomogram averaging

Florian M. Rossmann and Morgan Beeby*

Department of Life Sciences, Imperial College London, London SW7 2AZ, England. *Correspondence e-mail:

m.beeby@imperial.ac.uk

In situ structural information on molecular machines can be invaluable in

understanding their assembly, mechanism and evolution. Here, the use of

electron cryotomography (ECT) to obtain significant insights into how an

archetypal molecular machine, the bacterial flagellar motor, functions and how it

has evolved is described. Over the last decade, studies using a high-throughput,

medium-resolution ECT approach combined with genetics, phylogenetic

reconstruction and phenotypic analysis have revealed surprising structural

diversity in flagellar motors. Variations in the size and the number of torque-

generating proteins in the motor visualized for the first time using ECT has

shown that these variations have enabled bacteria to adapt their swimming

torque to the environment. Much of the structural diversity can be explained in

terms of scaffold structures that facilitate the incorporation of additional motor

proteins, and more recent studies have begun to infer evolutionary pathways to

higher torque-producing motors. This review seeks to highlight how the

emerging power of ECT has enabled the inference of ancestral states from

various bacterial species towards understanding how, and ‘why’, flagellar motors

have evolved from an ancestral motor to a diversity of variants with adapted or

modified functions.

1. Introduction

Understanding how molecular machines evolve is important

for reasons ranging from antibiotic design to synthetic biology.

The bacterial flagellar motor is an ideal model system for

probing the principles of molecular evolution. The flagellar

motor powers the rotation of bacterial flagella, which are

helical proteinaceous filaments extending from the bacterial

cell body that act as propellers for bacterial propulsion

through liquid medium or swarming across surfaces (Jarrell &

McBride, 2008). The flagellar motor is widespread, enabling

cross-species comparison, and well characterized in terms of

its components and function (Ohnishi et al., 1997; Imada et al.,

2016; Khan et al., 1992; Thomas et al., 2006), opening the way

for deeper questions on molecular evolution.

Structure determination of molecular machines such as the

flagellar motor is crucial to fully understand how they have

evolved. Electron cryomicroscopy (cryo-EM) has become the

technique of choice to gain structural insights into such large

macromolecular complexes. While single-particle analysis

cryo-EM (SPA) involves the purification of protein complexes

for imaging (Bai et al., 2015; Passmore & Russo, 2016), a

related technique called electron cryotomography (ECT)

together with subtomogram averaging (STA) can be used to

obtain three-dimensional structures of molecular machines in

situ without requiring a large number of particles (Ferreira et

al., 2018; Oikonomou & Jensen, 2017; Briggs, 2013). ECT

ISSN 2059-7983

involves flash-freezing intact cells and imaging them over a

range of angles, while maintaining them in a frozen state, in an

electron microscope. The resultant data set can be used to

calculate a three-dimensional reconstruction of the sample, or

tomogram. Subsequently, identical particles from multiple

tomograms can be extracted, computationally aligned and

averaged, yielding a three-dimensional reconstruction of the

particle of interest with a higher signal-to-noise ratio, a tech-

nique that is particularly valuable for many membrane-

associated machines that are difficult to purify intact.

Here, we review how ECT has contributed to our under-

standing of bacterial flagellar evolution by describing ECT,

how the ECT workflow has been optimized to image these

relatively low-abundance particles, and the resulting insights

into motor diversity and evolution. We start with an overview

of ECT and STA, outline how sample preparation, data

collection and data analysis have been optimized for the

problem, and describe how ECT has contributed to the

understanding of flagellar motor diversity and evolution.

2. Electron cryotomography and subtomogramaveraging

ECT is a technique that spans scales from structural biology to

cell biology (Fig. 1). Cryo-EM involves the vitrification of a

specimen by rapid freezing, preventing the formation of

damaging ice crystals. This results in a sample suspended in a

thin layer of vitreous ice that immobilizes the sample in a

hydrated, close-to-native state that is stable for imaging in an

electron cryo-microscope (Dubochet, 2012). Unlike conven-

tional transmission electron microscopy, which requires

chemical fixation and staining of the specimen, contrast in

cryo-EM is derived from induced phase contrast of biological

material in the microscope. Two major approaches are applied

to obtain the molecular structure of large proteins or protein

complexes using cryo-EM: SPA and ECT. SPA involves

imaging many thousands of identical purified particles that are

randomly oriented in vitreous ice. Given sufficient different

orientations, it is possible to reconstruct a three-dimensional

structure from these many two-dimensional images, in the

process averaging out noise. Recent improvements in the

developments of direct electron detectors have enabled full

realization of this potential: the so-called ‘resolution revolu-

tion’ (Grigorieff, 2013; Ruskin et al., 2013; Kuhlbrandt, 2014).

SPA can now provide very high resolution structures of

protein complexes (2–4 A).

ECT, unlike SPA, offers the ability to determine macro-

molecular structures such as the flagellar motor in their native

crowded cellular context. Although SPA is capable of high-

resolution structure determination, it requires purification of

the sample outside the cellular environment. ECT, on the

other hand, enables the study of large molecular machines in

vivo. In ECT, the sample is tilted over a range of angles in the

electron microscope and images are acquired at each step;

the resulting tilt series is subsequently reconstructed into a

three-dimensional tomogram of the specimen. Although the

collection of a single tomogram typically takes 10–60 min,

meaning that data acquisition is considerably slower than that

in SPA, insights can be obtained into the three-dimensional

architecture of unique specimens such as intact cells, enabling

the extrapolation of details of individual components of the

specimen that would be lost from a single two-dimensional

projection image, and distinguishing the cellular context from

the specimen of interest.

Individual tomograms have high levels of noise, necessi-

tating strategies to extract the signal. The sensitivity of the

specimen to ionizing electron radiation necessitates restriction

of the electron dose during imaging, leading to individual

tomograms with noise levels that obscure high-resolution

information. Noise can be reduced by averaging the infor-

mation from many identical structures across multiple tomo-

grams. The structures of interest, referred to as particles, can

be aligned using salient low-resolution features that are

readily identifiable even under high-noise conditions and

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586 Rossmann & Beeby � High-throughput electron cryotomography of bacterial motors Acta Cryst. (2018). D74, 585–594

Figure 1Schematic depicting electron cryotomography and subtomogram averaging of rare particles in the structural biology continuum. ECT bridges the gapbetween high-resolution structural biology techniques requiring the presence of a high abundance of particles and the low-resolution techniques used incell biology. (EM, electron microscopy; MD, molecular dynamics; NMR, nuclear magnetic resonance spectroscopy; SPA, single-particle analysis.)

averaged, ‘washing out’ noise to significantly improve the

signal-to-noise ratio. At best, such an approach enables access

to high-resolution signal at ‘near-atomic’ resolution (<4 A;

Turonova et al., 2017), although resolutions are more typically

in the nanometre range (Hu et al., 2017; Beeby et al., 2016).

This process is called subtomogram averaging.

The use of ECT and STA has a number of advantages.

Firstly, in situ imaging avoids the need for the development of

bespoke purification protocols for variants of a specimen from

mutants or different organisms. In addition, vitrification of a

living cell provides a snapshot of a fully functional cell and its

constituent machinery. Furthermore, tomograms provide

additional information about the cell-biological context of a

specimen, such as transient interactions with membranes,

peptidoglycan or transiently interacting partners. ECT can

also visualize fragile assembly intermediates and the hetero-

geneity of molecular machines in situ that would not be

possible to purify, enabling routine genetic manipulation to

perturb structure and function.

ECT with STA has become a powerful technique for

determining the structures of bacterial flagellar motors, and

their variants and mutants, to ‘macromolecular’ resolution (1–

5 nm). Although sufficient particles in extremely thin samples

can achieve resolutions below 4 A (Turonova et al., 2017), the

limited abundance of flagellar motors and the thickness of the

cell currently makes it difficult to improve upon nanometre

resolutions. To achieve this, optimization of sample prepara-

tion, automation of data acquisition, automation of tomogram

reconstruction and a streamlined subtomogram averaging

pipeline have been developed (Fig. 2).

2.1. Sample selection and preparation

In bacterial tomography projects, it is essential to select a

model system suitable for the collection of sufficient high-

quality data to produce a subtomogram average of sufficient

resolution. This requires the initial screening of possible

candidate species, and not all interesting model organisms are

suitable for further analysis. As vitrification of bacterial cells

on electron-microscopy grids requires cultures with high cell

densities, it must be possible to grow or concentrate the

bacteria to a high cell density. Furthermore, the species must

assemble sufficient functional flagella. Overexpression of

transcriptional regulators or certain flagellar proteins or the

deletion of negative regulators have successfully been used to

increase the number of particles per cell (Liu et al., 2012; Zhu

et al., 2017). Purification or enrichment protocols can further

increase the number of flagellated cells, such as density-

centrifugation approaches for minicells, as described fully

below.

Because noise in cryo-EM images is a product of the

thickness of the sample and its vitreous envelope, careful

selection of the model bacterium plays a role in reducing

specimen and ice thickness. Thin bacteria, and bacteria with

lower turgor pressure that have a tendency to flatten in the

thin layer of vitreous ice, are therefore amenable to ECT

(Beeby et al., 2016), leading to considerably thinner specimens

along the axis of the electron beam. Flagella positioned at

bacterial poles are also preferable to lateral flagella owing to

the fact that, when oriented correctly, pole thickness does not

increase as much upon tilting. Alternatively, genetic manip-

ulation of genes involved in the cell-division machinery can

generate thin, flagellated minicells (Farley et al., 2016; Liu et

al., 2012). Optimizing the growth medium can also produce

thinner cells (Chien et al., 2012) or reduce clumping (Calleja,

2017), leading to decreased ice thickness and making motors

more accessible for imaging. Screening many candidate

species under different conditions with conventional negative-

stain TEM techniques allows the selection of optimally thin

bacteria with many flagella.

After identifying an optimal strain, the next parameter to

maximize is the number of targets on an individual electron-

microscopy grid. This optimization allows the generation of

grids with hundreds of targets for tilt-series acquisition,

maximizing the time for data collection and minimizing the

time required to change grids in the microscope. Prior to

vitrification, the sample is applied onto an electron-

microscopy grid: a copper or gold grid consisting of 40–50 mm

squares covered with a thin support film of carbon or gold.

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Acta Cryst. (2018). D74, 585–594 Rossmann & Beeby � High-throughput electron cryotomography of bacterial motors 587

Figure 2Illustration of the general workflow of ECT and STA to study bacterialflagellar motors. Schematic showing the different steps including samplepreparation, data acquisition, tomogram reconstruction and subtomo-gram averaging. Samples are plunge-frozen in liquid cryogen, transferredto the microscope for the acquisition of images of cells over a range ofangles and computationally reconstructed to form a tomogram; finally,identical structures from different cells are superimposed and averaged toyield a subtomogram average.

Support films have micrometre-scale holes in them, in which

bacterial cells accumulate, allowing direct imaging of the cells

without additional scattering of the electron beam through the

support film. A few microlitres of bacterial suspension are

applied to the grid, and excess liquid is removed using blotting

paper, resulting in bacteria suspended in holes in the grid in a

thin film of liquid. Iterative optimization of the blotting

parameters is necessary for each sample to develop a reliable

protocol for the generation of grids with hundreds of tomo-

graphy targets. Vitrification robots help to maintain repro-

ducible conditions and allow quantitative and reproducible

settings for the blotting parameters to be found. Specifically,

adjustment of the blotting time and the force of blotting

maximizes the area of vitreous ice that is usable for tilt-series

acquisition on the grid. In order to subsequently reconstruct

tomograms from tilt series, nanoscale gold fiducial markers are

also usually added to the sample immediately prior to vitrifi-

cation. Optimization of the gold fiducial preparation leads to a

reproducible, even distribution of a large number of fiducials

per tomogram. Ethane cooled by liquid nitrogen can be used

for vitrification; alternatively, a mixture of ethane and propane

can be used, avoiding the need to monitor and control the

ethane temperature to avoid ethane freezing near liquid-

nitrogen temperatures (Tivol et al., 2008).

2.2. Optimization of data acquisition and processing

Streamlined data-acquisition pipelines are critical to facil-

itate rapid and reliable targeting. The use of high-throughput

data-acquisition software such as Leginon (Suloway et al.,

2009) or UCSF Tomo (Zheng et al., 2009) follows a ‘low-dose’

philosophy in which low electron-dose images are acquired

once and stored for subsequent targeting, circumventing the

need to expose parts of the grid to the electron beam multiple

times. Such an approach facilitates a streamlined targeting

process in which a mosaic of low-magnification images can be

collected of the entire grid, enabling the construction of a ‘grid

atlas’ montage to provide an overview of the entire grid for the

iterative targeting of higher magnification images of grid

squares, grid holes and targets for tilt-series acquisition.

Electron-microscope presets describing the complete config-

uration of the microscope at different magnifications can be

developed for optimal targeting at each preset magnification.

Such an approach ensures that only cells with suitably

oriented flagella are targeted.

Image contrast in the electron microscope is less straight-

forward than in a visible-light microscope (Ferreira et al.,

2018). Biological samples in an electron microscope provide

little amplitude contrast, and phase contrast is negligible when

the sample is focused within the electron microscope. When

the image is underfocused, however, phase contrast becomes

appreciable, although contrast varies as a function of defocus

and the resolution of features, as mathematically described by

the so-called ‘contrast transfer function’ (CTF). In broad

terms, higher defocus values provide higher signal at lower

resolutions but reduced signal at higher resolutions; since the

lower resolution features of particles are required for accurate

alignment, data-collection settings must balance defocus to

optimize the ability to align samples but also retain sufficient

high-resolution data. Furthermore, while increased electron

dose increases the signal-to-noise ratio of an image, the

ionizing nature of electrons means that too high a dose leads

to specimen damage and therefore degraded image quality,

meaning that the electron dose must be optimized.

Imaging low-abundance particles such as bacterial flagellar

motors by ECT also requires adaptations in the data-acquisi-

tion process. Data-collection parameters such as defocus,

magnification, electron dose and tilt scheme can be optimized

to best address the biological question. For ‘macromolecular’

resolution (�1–5 nm) subtomogram averages, a relatively high

cumulative electron dose (of between 60 and 120 e� A�2) and

rapid data-collection settings can be chosen, attaining a

balance weighted towards higher contrast at the expense of

losing higher resolution details; for higher resolution recon-

structions it may be necessary to reduce the dose and corre-

spondingly collect more data. The nominal defocus must also

be adjusted depending on the desired resolution. While a low

defocus of around�1 or�2 mm yields higher resolution STAs,

a higher defocus improves the contrast for the alignment of

particularly noisy data and simplifies particle picking.

Adjustment of the number and angular distribution of images

in a tilt series is particularly important to decrease the data-

collection time so as to acquire sufficient numbers of particles.

While smaller tilt increments increase the resolution of the

tomogram (Crowther et al., 1970), they also extend the

acquisition time and require a reduction of the electron dose

per frame. Depending on the sample and the intended reso-

lution, the tilt increment in conventional tomography typically

ranges from 0.5 to 5� (Hagen et al., 2017). A tilt increment of

<3� increases the data-acquisition time and the required data-

storage space. A further reduction in data-acquisition time

can be achieved by decreasing the maximum tilt angle.

Nevertheless, these optimizations lead to a data-collection

time of at least 10–15 min per tomogram. To collect a sufficient

amount of particles, multi-day data-collection sessions are still

necessary.

2.3. Reconstruction

The manual reconstruction of hundreds of tomograms with

few particles is time-consuming and laborious, demanding

automation. Scripts enable the pipelining of various applica-

tions (Morado et al., 2016) such as fiducial tracking with

RAPTOR (Amat et al., 2008), image processing with the

IMOD package (Kremer et al., 1996) and rapid reconstruction

algorithms (Agulleiro & Fernandez, 2011), facilitating the fast

calculation of tomographic reconstructions to process a large

quantity of tomographic data. Although medium-resolution

structure determination does not always implement the

correction of the perturbation by the CTF of features at

different resolutions (for a more in-depth discussion, see

Ferreira et al., 2018), it can also significantly improve the

resolution of STAs. Multiple software packages such as

Dynamo (Castano-Dıez et al., 2012; Castano-Dıez, 2017),

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PEET (Heumann et al., 2011; Nicastro, 2006), PyTOM (Hrabe

et al., 2012) and RELION (Scheres, 2012) can then be used to

obtain high-quality subtomogram averages.

3. Subtomogram averaging reveals considerablestructural diversity in bacterial flagellar motors

One of the most amenable systems to tomography, which

has yielded considerable biological insights, is the bacterial

flagellar motor (Fig. 3). The flagellar motor is a molecular

rotary motor centred around a core cytoplasmic stator–rotor

interaction that drives the rotation of a helical extracellular

propeller through torque transmitted across the periplasm by

an axial driveshaft (Chevance & Hughes, 2008). The stator

component is a ring of inner membrane-embedded motor-

protein ion channels immobilized by binding to the peri-

plasmic peptidoglycan; ion flux drives interaction with the

cytoplasmic rotor component called the C-ring. Torque

applied to the C-ring is transmitted across the periplasm via an

inner membrane-embedded MS-ring, which is connected to an

axial driveshaft: the rod. To traverse the peptidoglycan layer

and outer membrane, the rod passes through the P-ring and

the L-ring, respectively, which act as bushings, to connect to an

extracellular universal joint, called the hook, which finally

transmits torque to the multimicrometre-long helical

propeller: the flagellar filament. All axial structures are

assembled by an integral flagellar type 3 secretion system

(T3SS), with inner membrane components housed within the

MS-ring together with a cytoplasmic ATPase. Until recently,

much of what was known about the flagellar motor was

derived from biochemical (Altegoer & Bange, 2015), genetic

(Chevance & Hughes, 2008) and structural studies of purified

components (Thomas et al., 2006), preventing mechanistic

insights into the whole, assembled molecular machine, and

furthermore the majority of studies focused exclusively on the

motor from the model enteric bacteria Salmonella enterica and

Escherichia coli, preventing comparative insights.

Advances in ECT over the past decade have led to the

observation of large, unexpected variations in flagellar motor

structure (Fig. 3). The first in situ structure was determined in

the spirochaete Treponema primitia from 20 motors, reaching

a resolution of approximately 7 nm (Murphy et al., 2006).

Compared with the known flagellar structure of purified

Salmonella motors (Thomas et al., 2006), the T. primitia

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Figure 3The architecture of bacterial flagellar motors reveals considerable structural diversity. Top left: schematic of the flagellar motor. Top right, middle andbottom row: micrographs show central slices (100 � 100 nm) of subtomogram averages of C. crescentus, H. gracilis (Chen et al., 2011); V. fischeri (Beebyet al., 2016); S. putrefaciens; S. enterica, C. jejuni (Beeby et al., 2016); W. succinogenes (Chaban et al., 2018); H. hepaticus (Chen et al., 2011); H. pylori (Qinet al., 2016); B. bacteriovorus, A. butzleri (Chaban et al., 2018); Leptospira interrogans (Zhao et al., 2014); B. burgdorferi (Zhao et al., 2013); T. primitia(Murphy et al., 2006). Components are labelled as follows: B, basal disk; C, C-ring; H, H-ring; HF, hook/filament; IM, inner membrane; LP, L/P-ring; M,medial disk; MS, MS-ring; OM, outer membrane; P, proximal disk; P-c, P-collar; PG, peptidoglycan layer; R, rod; S, stators; T, T-ring; T3SS, type 3secretion system.

structure, and structures from related Borrelia species (Liu et

al., 2009; Kudryashev et al., 2009), obtained using ECT and

subtomogram averaging revealed that despite the conserved

core structure, the overall architecture of the flagellar motor

might be more diverse than previously expected. This was

confirmed by a subsequent study comparing the flagellar

motors from 11 bacterial species, revealing that in most

bacteria the conserved parts of the flagellar motor resemble

the E. coli and Salmonella-type motor structure, including the

characteristic tripartite densities representing the rings of the

export apparatus inside the cup-like structure of the cyto-

plasmic C-ring and the rod with P- and L-rings (Chen et al.,

2011), but also exhibit diverse additional structures that are

discussed in more detail below.

Despite a conserved core, however, variation was also

observed in the dimensions of these core components. The

diameter of the C-ring varied between different species,

ranging from 34 nm in Caulobacter crescentus to 57 nm in

T. primitia (Fig. 3). Correspondingly, some bacteria were also

observed to have distinctive stator-ring structures with vari-

able radii and symmetries above the inner membrane aligned

with the C-ring (Chen et al., 2011; Murphy et al., 2006). These

are clearly absent in enteric bacteria but are visible in Vibrio

cholerae (Chen et al., 2011). This corresponds to results indi-

cating that stator complexes are dynamic in enteric motors

(Leake et al., 2006; Fukuoka et al., 2009; Baker & O’Toole,

2017), in contrast to the high-occupancy or static anchoring

observed in Campylobacter and Vibrio. However, the bio-

logical significance of the variations in the presence of a stator

density, its symmetry and radius, and the corresponding

variations in C-ring size remain unknown at the time of this

study.

Strikingly, additional disk-like densities were found in the

periplasmic regions of many flagellar motors: larger ones in

"-proteobacteria such as Campylobacter jejuni and Helico-

bacter sp. and smaller ones in Shewanella putrefaciens, Vibrio

sp., Hylemonella gracilis (Chen et al., 2011) and Bdellovibrio

bacteriovorus (Chaban et al., 2018) (Fig. 3). The motors of the

periplasmic flagellated spirochetes T. primitia and Borrelia

burgdorferi discussed above exhibit large outward-facing

collar structures in the cytoplasm above the inner membrane

(Liu et al., 2009; Kudryashev et al., 2009; Murphy et al., 2006;

Fig. 3). At the time, the role of these additional structures

composed of unidentified accessory proteins was also unclear.

4. A central assay: deletion mutants to understandmotor architecture

Although these advances in in vivo structure determination

allowed the determination of the architecture of intact

flagellar motors, the specific locations of proteins remained

inferences from previous knowledge, leaving it difficult to

decipher the locations of proteins within the in situ archi-

tecture.

One approach to locate a protein in a tomogram is to

generate an in-frame deletion of the corresponding gene and

reimage the flagellar motor of the deletion mutant. The

resulting subtomogram average can then be compared with

the wild-type structure of the motor and examined for loss of

density that may indicate the location of the protein in ques-

tion (Figs. 4a and 4b). This method was first used to identify

the location of a cytoplasmic ATPase component of the T3SS

which is responsible for flagellar assembly, FliI (Fan &

Macnab, 1996; Chen et al., 2011). The structure of a C. jejuni

mutant strain lacking fliI, which nevertheless produced suffi-

cient motors for subtomogram averaging, lacked the lowest,

cytoplasmic density of the T3SS of the C. jejuni wild-type

structure (Fig. 4a). Combined with previous knowledge about

the structure of the T3SS, this indicated a putative location of

FliI at the base of the flagellar motor (Chen et al., 2011).

This technique has subsequently been used in many studies

to locate individual protein components within flagellar

motors. The next protein to be located was the integral

membrane protein FlhA, a core component of the flagellar

T3SS with a large C-terminal cytoplasmic domain. In C. jejuni,

truncation of flhAC caused a cytoplasmic ring structure above

FliI to disappear (Fig. 4a), indicating that FlhA forms a

toroidal component that mediates the interaction of the FliI–

ATPase complex with the transmembrane T3SS. Indeed,

correspondingly, this ring density fitted the nonameric ring of

an X-ray structure of an FlhA orthologue from the Shigella

flexneri injectisome (Abrusci et al., 2013). Building on these

results, multiple deletion mutants from B. burgdorferi were

used to reveal the molecular architecture and sequential

assembly process of flagellar motors (Zhao et al., 2013). The

location of stator-associated accessory proteins, such as FliL in

B. burgdorferi (Motaleb et al., 2011), MotAB and MotXY in

Vibrio sp. (Beeby et al., 2016; Zhu et al., 2017; Fig. 4b) and

MotAB and PflAB in C. jejuni (Beeby et al., 2016; Fig. 4a),

have also confirmed the use of this technique, as discussed

further below.

5. Structural diversity provides a clear selective benefit:higher torque

The ability to locate specific proteins in a subtomogram

average allowed a deeper investigation of the function of

additional structures in diverse flagellar motors composed of

accessory proteins. Towards understanding motor evolution, a

recent study probed the selective benefits of motor diversity,

finding that additional motor structures serve as a scaffold to

assemble larger motors that output higher torque. Torque is a

measurement of rotary force, and it follows that higher

torques will enable propulsion through more viscous media

that would otherwise immobilize motors that produce lower

torque. Motor torque varies substantially between different

bacteria and correlates with their swim speed and ability to

propel themselves in highly viscous media such as gastro-

intestinal mucus. Three different bacteria that produce

different torques were compared using electron cryotomo-

graphy in an effort to rationalize different torque outputs:

Salmonella with �1300 pN nm torque output, Vibrio with

�2000 pN nm and C. jejuni with �3600 pN nm. Using the

selective deletion strategy, ECT of V. fischeri and C. jejuni not

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only verified the location of the stator ring in the motor

structure but also enabled determination of the number of

stator complexes in the stator ring. Strikingly, the number of

stator complexes, and their radius from the axis of rotation,

differed in these higher torque-generating species from the

�11 stator complexes in Salmonella positioned �20 nm from

the axis of rotation (Reid et al., 2006; Leake et al., 2006):

V. fischeri had 13 stator complexes located at a radius of

21.5 nm from the rod, while C. jejuni had 17 stator complexes

located 26.5 nm from the rod, and the C-rings were also

correspondingly wider in both. Indeed, the number and the

location of the stator complexes, combined with previously

measured stator-complex force exertion, was sufficient to

accurately quantitatively predict the torque outputs of struc-

turally diverse bacteria (Beeby et al., 2016).

The protein components of the additional structures have

also been determined and located by deletion analysis. In

Vibrio species FlgP has been shown to form a large ‘basal disk’

beneath, and interacting with, the outer membrane (Fig. 4b).

Intriguingly, in C. jejuni a homologous, although larger, FlgP-

based basal disk also assembles under the outer membrane; a

protein lattice composed of FlgQ and PflAB subsequently

assembles between the basal disk and the outer membrane

(Fig. 4a). In both species, assembly of the wider stator ring first

requires assembly of the scaffold structures, indicating that the

primary role of the accessory proteins is to scaffold wider rings

of additional stator complexes to exert higher torque (Beeby

et al., 2016).

While Vibrio and C. jejuni assemble FlgP-based stator

scaffolds, parallel studies in spirochaetes suggest that high

torque output has convergently evolved independently in this

lineage using alternative protein building blocks other than

FlgP. Spirochaete lifestyle is unusual: many are pathogens and

all have flagellar filaments that coil around the cell body

within the periplasm instead of passing across the outer

membrane, and motor rotation is believed to drive gyration of

the cell body to bore through host mucus and tissues (Charon

et al., 2012). Spirochaete motors are thought to output the

highest torque yet discovered, rotating with a torque of

�4000 pN nm. Spirochaete motors have a C-ring that is

considerably wider than that seen in enteric motors, and 16

putative stator-complex densities are observed in a ring of

corresponding width. Taken together, the location and

number of stator complexes accurately predicts the measured

torque of spirochaete motors (Beeby et al., 2016). Whereas the

FlgP-based structures form a set of stacked disks in Vibrio and

C. jejuni that are responsible for wider stator-complex rings, in

spirochete flagellar motors a large cup-shaped structure is

seen intermediate between the rod and the stator complexes

and is referred to as the P-collar (Murphy et al., 2006). A

comparative genomics approach identified a protein, FlbB, as

a candidate component of the P-collar (Chen et al., 2011), a

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Acta Cryst. (2018). D74, 585–594 Rossmann & Beeby � High-throughput electron cryotomography of bacterial motors 591

Figure 4ECT and STA of deletion mutants helps to locate individual proteins within the overall motor architecture. Micrographs show central slices (100 �100 nm) of subtomogram averages of C. jejuni (a) and V. fischeri (b) wild type and deletion mutants. Arrows point at the putative location of therespective, deleted protein that can be determined by comparison with other mutants and established biochemical data (Beeby et al., 2016; Abrusci et al.,2013; Chen et al., 2011).

prediction that was subsequently confirmed by deletion

imaging (Moon et al., 2016). As with FlgP and its associated

proteins, deletion of FlbB leads to a loss of motility and failure

of the stator complexes to incorporate into the motor,

suggesting that spirochaetes have independently evolved a

stator-complex scaffold structure to produce higher torque to

facilitate their unusual lifestyle. Intriguingly, however, FlbB is

only approximately 200 amino acids in length and therefore

additional components are likely to be identified in the future.

6. Combining subtomogram averaging withphylogenetics illuminates possible evolutionary pathsto higher torque

Subsequent studies have sought to understand how these high-

torque motors evolved. Naively, these motors are ‘irreducibly

complex’ in that they are nonfunctional upon the deletion of

individual components. Indeed, many of these components

were first identified by screening for nonmotile motors

resulting from mutations in genes that were not encoded in

organisms with simpler motors.

A recent study revealed that the protein PflB enables the

formation of the wider stator rings observed in H. pylori and

C. jejuni (Chaban et al., 2018). Phylogenetic analysis of

bacterial species identified the descendants of intermediary

ancestral states for ECT and STA imaging, resulting in

visualization of the additional protein densities and their

effect on the size of the stator ring in motors from different

species. According to the established location of the accessory

proteins in C. jejuni, identities could be assigned to additional

densities in motor structures. Consistently, motility assays in

media of different viscosities demonstrated a correlation

between motor-torque output and stator-ring radius. Not only

did this confirm that wider stator rings with additional stator

units produce higher torque, but it also demonstrated that

bacterial species lacking PflB have significantly reduced stator

width and a correspondingly lower swimming ability. While

S. enterica probably only possesses up to 11 stator units (Reid

et al., 2006; Leake et al., 2006), B. bacteriovorus encodes a

possible distant homologue of PflA, but not PflB, and exhibits

a corresponding putative PflA disk structure that scaffolds the

incorporation of 12 stator units (Chaban et al., 2018). When-

ever PflB is present, however, the stator ring increases to

17 � 1 stator units: 16 stator units in Arcobacter butzleri, 17 in

C. jejuni and Wollinella succinogenes, and 18 in H. pylori

(Chaban et al., 2018).

These data also suggest a possible evolutionary pathway for

the acquisition of the accessory proteins seen in C. jejuni-type

motors (Fig. 5). Assuming an ancient flagellar motor with a

relatively simple motor structure, as found in E. coli or

S. enterica, the first step involves the emergence of a peri-

plasmic disk around the rod just above the inner membrane

which scaffolds and stabilizes the stator ring. Indeed, this has

occurred independently at least three times and includes

MotXY forming the T-ring in Vibrio sp., unknown proteins in

H. gracilis and PflB in "-proteobacteria. In a second step, an

outer membrane-associated basal disk consisting of the

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592 Rossmann & Beeby � High-throughput electron cryotomography of bacterial motors Acta Cryst. (2018). D74, 585–594

Figure 5Proposed model for the evolution of the bacterial flagellar motor inferredfrom ECT and STA data. ECT and STA have indicated multiple pathwaysfor the acquisition of additional accessory proteins resulting in improvedstator support, increased outer membrane support and finally, in the caseof C. jejuni, a basal disk–proximal disk fusion. ECT has also revealedstructural and evolutionary insights into degenerate flagellar motors thathave become injectisomes: virulence-factor delivery systems that are usedby many pathogenic bacteria. Ancestral states have been inferred fromrepresentative subtomogram averages on the right coupled withphylogenetic studies (Chaban et al., 2018; Beeby et al., 2016).

protein FlgP was recruited; the exact role of this disk is unclear

but may be to act as an additional support anchored to the

outer membrane. In a third step these two disk structures fuse

to form the contemporary wider stator-complex scaffold. This

fusion step was effectively a functional sidestep for both

previously independent rings, which became mutually co-

dependent, i.e. irreducibly complex (Chaban et al., 2018).

7. Recent advances push resolution and reveal insightsinto the evolution of injectisomes as degenerateflagellar motors

Another intriguing aspect of flagellar evolution that ECT has

provided insights into is the degeneration of an ancestral

motor to form the hypodermic syringe-esque ‘injectisome’

complex used by many pathogens. Injectisomes, also referred

to as type III secretion systems, are used by diverse pathogens

to inject virulence factors into host cells to hijack their

physiology. Phylogenetic studies indicate that injectisomes are

degenerate flagella that have lost their stator complexes and

have adapted their flagellar filament to become a short, rigid,

hollow needle for virulence-factor delivery (Abby & Rocha,

2012; Fig. 5). ECT studies of injectisomes requires consider-

able sample optimization, as many pathogens (for example

Salmonella, E. coli and Yersinia species) are too thick for high-

resolution imaging. Successful studies have employed minicell

systems (Hu et al., 2015; Kawamoto et al., 2013) or selected

thin bacteria that are more amenable to imaging (Nans et al.,

2015).

One of the most significant contributions of ECT to

understanding injectisome function and evolution has been

the visualization of a remnant of the C-ring that is still critical

for injectisome function (Hu et al., 2015, 2017). This insight

required high-resolution technical tour-de-force studies,

necessitating the collection of an order of magnitude more

data than most previous studies. In the highest resolution

study to date, the structure of the Salmonella SPI-1 injecti-

some was determined to 17 A resolution (Hu et al., 2017). To

achieve this result, genetic techniques were used to produce

Salmonella minicells with increased numbers of injectisomes,

and tilt series were acquired using dose fractionation, motion

correction and automated reconstruction of CTF-corrected

data. The unprecedented 17 A resolution final average was

composed of thousands of subtomograms and provided high-

resolution images of the composition of the vestigial C-ring.

This and other studies demonstrate that this vestigial C-ring

no longer forms a ring but rather a ring of six ‘pods’. The

flagellar C-rings function to anchor the FliI ATPase complex

and sort export substrates in addition to rotation and direc-

tional switching, and it is clear that the injectisome has

retained a vestigial C-ring to retain these functions that are

essential for assembly and virulence-factor secretion.

8. Future prospects

Future prospects for understanding bacterial flagellar motors

are significant as the capabilities of ECT continue to mature.

The deliverables from ECT are fairly straightforward: better

data, and more of it. The impacts of these deliverables will

be major advances in understanding flagellar assembly,

mechanism and evolution.

The most immediate contributor to higher resolution

subtomogram averages will be higher quality tilt-series images,

producing higher resolution tomograms and in turn producing

higher resolution subtomogram averages. The introduction of

improved direct electron detector cameras will be the most

significant aspect of higher resolution images. The combina-

tion of robust phase plates and energy filters will further

improve resolution by boosting the signal-to-noise ratio and

the contrast in tomograms, enabling image acquisition closer

to focus yet with high contrast (Fukuda et al., 2015). This

would allow the collection of higher resolution tilt series with

lower electron doses, resulting in reduced electron damage.

Nevertheless, recent algorithms to compensate for electron-

induced specimen warping promise to mitigate for some

aspects of electron damage (Fernandez et al., 2018). Further-

more, three-dimensional CTF correction will fully compensate

for resolution attenuation resulting from ignoring defocus

modulation as a function of sample depth (Turonova et al.,

2017). Finally, a recently developed, improved tilt scheme

provides better data (Hagen et al., 2017) which may be further

optimized.

Faster data acquisition will synergize with higher quality

images to produce higher resolution subtomogram averages.

Higher frame-rate direct electron detectors will not only

provide better motion correction and faster image acquisition,

but also enable the development of stable tilt stages that are

capable of collecting tilt series in seconds not minutes. Such an

increase in throughput will enable the routine collection of

thousands of cryotomograms and will pave the way for routine

subnanometre structural determination. Such rapid data

collection will also require reliable sample preparation (for

example the SpotItOn approach; Jain et al., 2012), the ability

to seamlessly switch between grids during a data-collection

session, and algorithms for automated target selection.

Even with the advances described above, it may not always

be possible to accurately build a pseudo-atomic model into

subtomogram average structures, and a range of hybrid

methods will need further development. Deletion analysis has

been invaluable to recent studies, but is inherently limited in

its capability to positively identify a structure; the develop-

ment of a robust tagging system to rationally insert additional

domains for positive identification will be important.

Furthermore, coevolutionary approaches to identify protein

binding surfaces will reduce the ambiguity in modelling

binding interfaces.

These developments promise to facilitate significant

insights. Given the ability to acquire in situ structures to

subnanometre resolution, the gap between structural and

cellular biology will be bridged, enabling the construction of

complete pseudo-atomic models of flagellar motors to

understand their molecular mechanisms. As seen with the

resolution revolution in single-particle analysis, the ramifica-

tions of faster data collection will be considerable and go

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Acta Cryst. (2018). D74, 585–594 Rossmann & Beeby � High-throughput electron cryotomography of bacterial motors 593

beyond simply reducing the time required to collect a data set,

rendering previously intractable questions about flagellar

mechanism and evolution possible.

Funding information

This work was supported by BBSRC grant BB/L023091/1 to

MB and a DFG research fellowship (project No. 385257318) to

FMR.

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